How SonarQube-identified technical debt is prioritized: An exploratory case study

Abstract

Context: Repaying all technical debt (TD) in a system may be unviable, as there is typically a shortage of resources allocated for TD repayment activities. Therefore, TD prioritization is essential to best allocate such limited resources. Fortunately, one can utilize a static code analysis tool, such as SonarQube, to aid in expediting the TD prioritization process. Objective: Given that SonarQube is one of the most utilized tools in the context of TD, this exploratory case study seeks to explore how SonarQube-identified TD items are perceived and prioritized for repayment. Methods: The study was designed, replicated, and conducted in four companies and a master's level course, with a total of 89 participants. The participants were requested to select TD items to include for repayment under a resources constraint. Results: The results revealed that the overwhelming majority of participants prioritized TD by factoring in a TD item's value and cost, a smaller number prioritized higher value TD items, and only one participant prioritized lower cost TD items. Furthermore, it was revealed that the value of a TD item is subjective and context-dependent, and the majority of participants perceive the cost estimations provided by SonarQube for repaying TD items to be reliable and trustworthy when prioritizing TD. Conclusion: Based on the results, one can conclude that there is no silver bullet TD prioritization approach that addresses all of a developer's objectives and needs. New TD prioritization approaches should be designed without concentrating on a specific prioritization perspective and should be independent of value estimation methods.